Arabic Dialect Identification(DID)is a task in Natural Language Processing(NLP)that involves determining the dialect of a given piece of text in Arabic.The state-of-the-art solutions for DID are built on various deep ...Arabic Dialect Identification(DID)is a task in Natural Language Processing(NLP)that involves determining the dialect of a given piece of text in Arabic.The state-of-the-art solutions for DID are built on various deep neural networks that commonly learn the representation of sentences in response to a given dialect.Despite the effectiveness of these solutions,the performance heavily relies on the amount of labeled examples,which is labor-intensive to atain and may not be readily available in real-world scenarios.To alleviate the burden of labeling data,this paper introduces a novel solution that leverages unlabeled corpora to boost performance on the DID task.Specifically,we design an architecture that enables learning the shared information between labeled and unlabeled texts through a gradient reversal layer.The key idea is to penalize the model for learning source dataset specific features and thus enable it to capture common knowledge regardless of the label.Finally,we evaluate the proposed solution on benchmark datasets for DID.Our extensive experiments show that it performs signifcantly better,especially,with sparse labeled data.By comparing our approach with existing Pre-trained Language Models(PLMs),we achieve a new state-of-the-art performance in the DID field.The code will be available on GitHub upon the paper's acceptance.展开更多
Objectives:By investigating the distinct speech and voice phenotype among TCM constitution for adults,this study aims at providing a convenient and objective methodological reference for judging TCM constitution.Metho...Objectives:By investigating the distinct speech and voice phenotype among TCM constitution for adults,this study aims at providing a convenient and objective methodological reference for judging TCM constitution.Methods:Acoustic analysis and TCM constitution assessment were performed for all 620 participants using Praat software and the CCMQ,respectively.Results:For formant features,the speech duration of special constitution participants was shorter than that of neutral,phlegm-dampness,dampness-heat,Yin-deficiency,or Yang-deficiency participants when pronuncing the vowels/a/,/i/,and/u/.Compare to Yang-deficiency,Qi-deficiency participants had a shorter speech duration when pronucing/i/.For/u/,blood-stasis participants exhibited a lower F1 value than neutral participants.For vocal features,special constitution participants showed higher local jitter than neutral,dampness-heat,and Yang-deficiency participants(for/a/,/i/,and/u/).Higher absolute local jitter than neutral or dampness-heat participants.Compared with neutral or Yang-deficiency participants,special participants owned a higher local shimmer(dB).Special participants had a lower harmonicity autocorrelation than neutral,dampness-heat,or Yang-deficiency participants.Conclusions:Formant features may effectively differentiate special constitution from neutral,phlegm-dampness,dampness-heat,Yin-deficiency,or Yang-deficiency constitutions based on vowel duration measurements(/a/,/i/,/u/).For the vowel/u/,F1 values may help distinguish blood-stasis from neutral constitution.Vocal features appear particularly useful for distinguishing special constitution from neutral,dampness-heat,or Yang-deficiency constitution,with local jitter and harmonicity autocorrelation showing significant discriminatory power.展开更多
Forests are essential for both ecological and economic aspects.Most rural people in developing countries rely on forest resources for their livelihood.Since 1980,trade has substantially affected forest cover,density,a...Forests are essential for both ecological and economic aspects.Most rural people in developing countries rely on forest resources for their livelihood.Since 1980,trade has substantially affected forest cover,density,and management in developing countries.Few studies have examined how changes in trade structure and international trade in primary commodities affect forest density.To better understand the relationship between trade,trade structure adjustment,and forest density,this study examined 52 developing countries across four income levels:high income(HI),low income(LI),upper-middle income(UMI),and lower-middle income(LMI).We compared studies on historical changes in forest cover with those on forest density.For alternative outcomes,we used a generalized method of moments(GMM)model for the entire panel and a random-effects model for various income categories.The results show that the percentage of non-primary goods exported(PNPEXP)and total manufacturing and services exported(TEXP)significantly impact forest density.This suggests that trade and trade structure can improve a country’s forest density conditions.展开更多
As global economic integration development enters a realization era,English holds a very important position in China's diplomacy as the language is an internationally-used language.Besides,English also plays a ver...As global economic integration development enters a realization era,English holds a very important position in China's diplomacy as the language is an internationally-used language.Besides,English also plays a very important role in our daily life.Colleges and universities should pay more attention in strengthening the development of English teaching courses as they are an important base for cultivating high-quality talents.In the modern teaching of English and American literature courses,college English majors do not only need to teach students English language knowledge but are also required need to strengthen students'knowledge and study of national culture.In this journal,the author investigates and analyses the current situation and existing problems of the modern teaching of English and American literature courses in English majors of colleges and universities.Then,puts forward the implementation strategies such as modern teaching of English and American literature courses in English majors’colleges and universities,aiming to help in implementing the teaching of English and American literature courses successfully.展开更多
As global economic integration development enters a realization era,English holds a very important position in China's diplomacy as the language is an internationally-used language.Besides,English also plays a ver...As global economic integration development enters a realization era,English holds a very important position in China's diplomacy as the language is an internationally-used language.Besides,English also plays a very important role in our daily life.Colleges and universities should pay more attention in strengthening the development of English teaching courses as they are an important base for cultivating high-quality talents.In the modern teaching of English and American literature courses,college English majors do not only need to teach students English language knowledge but are also required need to strengthen students'knowledge and study of national culture.In this journal,the author investigates and analyses the current situation and existing problems of the modern teaching of English and American literature courses in English majors of colleges and universities.Then,puts forward the implementation strategies such as modern teaching of English and American literature courses in English majors’colleges and universities,aiming to help in implementing the teaching of English and American literature courses successfully.展开更多
In the contemporary era,the death rate is increasing due to lung cancer.However,technology is continuously enhancing the quality of well-being.To improve the survival rate,radiologists rely on Computed Tomography(CT)s...In the contemporary era,the death rate is increasing due to lung cancer.However,technology is continuously enhancing the quality of well-being.To improve the survival rate,radiologists rely on Computed Tomography(CT)scans for early detection and diagnosis of lung nodules.This paper presented a detailed,systematic review of several identification and categorization techniques for lung nodules.The analysis of the report explored the challenges,advancements,and future opinions in computer-aided diagnosis CAD systems for detecting and classifying lung nodules employing the deep learning(DL)algorithm.The findings also highlighted the usefulness of DL networks,especially convolutional neural networks(CNNs)in elevating sensitivity,accuracy,and specificity as well as overcoming false positives in the initial stages of lung cancer detection.This paper further presented the integral nodule classification stage,which stressed the importance of differentiating between benign and malignant nodules for initial cancer diagnosis.Moreover,the findings presented a comprehensive analysis of multiple techniques and studies for nodule classification,highlighting the evolution of methodologies from conventional machine learning(ML)classifiers to transfer learning and integrated CNNs.Interestingly,while accepting the strides formed by CAD systems,the review addressed persistent challenges.展开更多
This article studies the influence of polymers on drag reduction and heat transfer enhancement of a nanofluid past a uniformly heated permeable vertically stretching surface. Our prime focus is on analyzing the possib...This article studies the influence of polymers on drag reduction and heat transfer enhancement of a nanofluid past a uniformly heated permeable vertically stretching surface. Our prime focus is on analyzing the possible effects of polymer inclusion in the nanofluid on drag coefficient, Nusselt number and Sherwood number. Dispersion model is considered to study the behavior of fluid flow and heat transfer in the presence of nanoparticles. Molecular approach is opted to explore polymer addition in the base fluid. An extra stress arises in the momentum equation as an outcome of polymer stretching. The governing boundary layer equations are solved numerically. Dependence of physical quantities of engineering interest on different flow parameters is studied. Reduction in drag coefficient, Nusselt number and Sherwood number is noticed because of polymer additives.展开更多
:Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and services.The increasing availability of such big data on biased reviews and blogs creates cha...:Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and services.The increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making process.To overcome this challenge,extracting suggestions from opinionated text is a possible solution.In this study,the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’reviews.A classification using a word-embedding approach is used via the XGBoost classifier.The two datasets used in this experiment relate to online hotel reviews and Microsoft Windows App Studio discussion reviews.F1,precision,recall,and accuracy scores are calculated.The results demonstrated that the XGBoost classifier outperforms—with an accuracy of more than 80%.Moreover,the results revealed that suggestion keywords and phrases are the predominant features for suggestion extraction.Thus,this study contributes to knowledge and practice by comparing feature extraction classifiers and identifying XGBoost as a better suggestion mining process for identifying online reviews.展开更多
The feedback collection and analysis has remained an important subject matter for long.The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis.However,the...The feedback collection and analysis has remained an important subject matter for long.The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis.However,the student expresses their feedback opinions on online social media sites,which need to be analyzed.This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews.Our technique computes the sentiment score of student feedback reviews and then applies a fuzzy-logic module to analyze and quantify student’s satisfaction at the fine-grained level.The experimental results reveal that the proposed work has outperformed the baseline studies as well as state-of-the-art machine learning classifiers.展开更多
Software crowdsourcing(SW CS)is an evolving software development paradigm,in which crowds of people are asked to solve various problems through an open call(with the encouragement of prizes for the top solutions).Beca...Software crowdsourcing(SW CS)is an evolving software development paradigm,in which crowds of people are asked to solve various problems through an open call(with the encouragement of prizes for the top solutions).Because of its dynamic nature,SW CS has been progressively accepted and adopted in the software industry.However,issues pertinent to the understanding of requirements among crowds of people and requirements engineers are yet to be clarified and explained.If the requirements are not clear to the development team,it has a significant effect on the quality of the software product.This study aims to identify the potential challenges faced by requirements engineers when conducting the SW–CS based requirements engineering(RE)process.Moreover,solutions to overcome these challenges are also identified.Qualitative data analysis is performed on the interview data collected from software industry professionals.Consequently,20 SW–CS based RE challenges and their subsequent proposed solutions are devised,which are further grouped under seven categories.This study is beneficial for academicians,researchers and practitioners by providing detailed SW–CS based RE challenges and subsequent solutions that could eventually guide them to understand and effectively implement RE in SW CS.展开更多
This essay will review the earliest case that documents a patient’s experience of qi,one found on a bamboo text buried with the patient who died in the 318 BCE.Details of the healing encounter and of concepts of illn...This essay will review the earliest case that documents a patient’s experience of qi,one found on a bamboo text buried with the patient who died in the 318 BCE.Details of the healing encounter and of concepts of illness show how non-transmitted documents hidden from later editors in tombs preserve an older layer of medical understanding than that in transmitted canons,such as the Huang Di Nei Jing(Inner Canon of the Yellow Emperor).The 4th-century BCE case record described below is the longest early medical record concerning the treatment of a specific individual.It is also an account of failure formally recorded for the sake of the survivors and buried with the dead to be transmitted to the world of the spirits.The essay begins with a reevaluation of ancient concept of qi and then moves on to the individual case record.展开更多
The Internet of Things(IoT)is gaining attention because of its broad applicability,especially by integrating smart devices for massive communication during sensing tasks.IoT-assisted Wireless Sensor Networks(WSN)are s...The Internet of Things(IoT)is gaining attention because of its broad applicability,especially by integrating smart devices for massive communication during sensing tasks.IoT-assisted Wireless Sensor Networks(WSN)are suitable for various applications like industrial monitoring,agriculture,and transportation.In this regard,routing is challenging to nd an efcient path using smart devices for transmitting the packets towards big data repositories while ensuring efcient energy utilization.This paper presents the Robust Cluster Based Routing Protocol(RCBRP)to identify the routing paths where less energy is consumed to enhances the network lifespan.The scheme is presented in six phases to explore ow and communication.We propose the two algorithms:(i)energy-efcient clustering and routing algorithm and (ii)distance and energy consumption calculation algorithm.The scheme consumes less energy and balances the load by clustering the smart devices.Our work is validated through extensive simulation using Matlab.Results elucidate the dominance of the proposed scheme is compared to counterparts in terms of energy consumption,the number of packets received at BS and the number of active and dead nodes.In the future,we shall consider edge computing to analyze the performance of robust clustering.展开更多
Throughout the use of the small battery-operated sensor nodes encou-rage us to develop an energy-efficient routing protocol for wireless sensor networks(WSNs).The development of an energy-efficient routing protocol is...Throughout the use of the small battery-operated sensor nodes encou-rage us to develop an energy-efficient routing protocol for wireless sensor networks(WSNs).The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of WSN.Many routing protocols are available,but the issue is still alive.Clustering is one of the most important techniques in the existing routing protocols.In the clustering-based model,the important thing is the selection of the cluster heads.In this paper,we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining energy and the distance of the nodes in each cluster.Initially,the bubble sort algorithm chose the two nodes with the maximum remaining energy in the cluster and chose a cluster head with a small distance.The proposed scheme performs hierarchal routing and direct routing with some energy thresholds.The simulation will be performed in MATLAB to justify its performance and results and compared with the ECHERP model to justify its performance.Moreover,the simulations will be performed in two scenarios,gate-way-based and without gateway to achieve more energy-efficient results.展开更多
With the advent and advancements in the wireless technologies,Wi-Fi ngerprinting-based Indoor Positioning System(IPS)has become one of the most promising solutions for localization in indoor environments.Unlike the ou...With the advent and advancements in the wireless technologies,Wi-Fi ngerprinting-based Indoor Positioning System(IPS)has become one of the most promising solutions for localization in indoor environments.Unlike the outdoor environment,the lack of line-of-sight propagation in an indoor environment keeps the interest of the researchers to develop efcient and precise positioning systems that can later be incorporated in numerous applications involving Internet of Things(IoTs)and green computing.In this paper,we have proposed a technique that combines the capabilities of multiple algorithms to overcome the complexities experienced indoors.Initially,in the database development phase,Motley Kennan propagation model is used with Hough transformation to classify,detect,and assign different attenuation factors related to the types of walls.Furthermore,important parameters for system accuracy,such as,placement and geometry of Access Points(APs)in the coverage area are also considered.New algorithm for deployment of an additional AP to an already existing infrastructure is proposed by using Genetic Algorithm(GA)coupled with Enhanced Dilution of Precision(EDOP).Moreover,classication algorithm based on k-Nearest Neighbors(k-NN)is used to nd the position of a stationary or mobile user inside the given coverage area.For k-NN to provide low localization error and reduced space dimensionality,three APs are required to be selected optimally.In this paper,we have suggested an idea to select APs based on Position Vectors(PV)as an input to the localization algorithm.Deducing from our comprehensive investigations,it is revealed that the accuracy of indoor positioning system using the proposed technique unblemished the existing solutions with signicant improvements.展开更多
Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention ...Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions.However,most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets,resulting in performance degradation.To overcome this issue,this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset.The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision,recall ad f-measure.Finally,a classifier with the best performance is recommended for the emotion classification.展开更多
In this article,we construct the most powerful family of simultaneous iterative method with global convergence behavior among all the existing methods in literature for finding all roots of non-linear equations.Conver...In this article,we construct the most powerful family of simultaneous iterative method with global convergence behavior among all the existing methods in literature for finding all roots of non-linear equations.Convergence analysis proved that the order of convergence of the family of derivative free simultaneous iterative method is nine.Our main aim is to check out the most regularly used simultaneous iterative methods for finding all roots of non-linear equations by studying their dynamical planes,numerical experiments and CPU time-methodology.Dynamical planes of iterative methods are drawn by using MATLAB for the comparison of global convergence properties of simultaneous iterative methods.Convergence behavior of the higher order simultaneous iterative methods are also illustrated by residual graph obtained from some numerical test examples.Numerical test examples,dynamical behavior and computational efficiency are provided to present the performance and dominant efficiency of the newly constructed derivative free family of simultaneous iterative method over existing higher order simultaneous methods in literature.展开更多
The paper focuses on the properties of relative pronouns in the acquisition of relative clause by Chinese EFL learners. Based on the NPAH （noun phrase accessibility hierarchy）, comparison and contrast of some aspect...The paper focuses on the properties of relative pronouns in the acquisition of relative clause by Chinese EFL learners. Based on the NPAH （noun phrase accessibility hierarchy）, comparison and contrast of some aspects of English and Chinese relative pronoun, the paper conducts two experiments, and has proved the hypotheses that students＇ performance generally follows the hierarchy of NPAH and students do have problems with relative pronoun involving prepositions. Besides, some pedagogical implications for foreign language teaching are discussed.展开更多
基金supported by the Deanship of Scientific Research at King Khalid University through Small Groups funding(Project Grant No.RGP1/243/45)The funding was awarded to Dr.Mohammed Abker.And Natural Science Foundation of China under Grant 61901388.
文摘Arabic Dialect Identification(DID)is a task in Natural Language Processing(NLP)that involves determining the dialect of a given piece of text in Arabic.The state-of-the-art solutions for DID are built on various deep neural networks that commonly learn the representation of sentences in response to a given dialect.Despite the effectiveness of these solutions,the performance heavily relies on the amount of labeled examples,which is labor-intensive to atain and may not be readily available in real-world scenarios.To alleviate the burden of labeling data,this paper introduces a novel solution that leverages unlabeled corpora to boost performance on the DID task.Specifically,we design an architecture that enables learning the shared information between labeled and unlabeled texts through a gradient reversal layer.The key idea is to penalize the model for learning source dataset specific features and thus enable it to capture common knowledge regardless of the label.Finally,we evaluate the proposed solution on benchmark datasets for DID.Our extensive experiments show that it performs signifcantly better,especially,with sparse labeled data.By comparing our approach with existing Pre-trained Language Models(PLMs),we achieve a new state-of-the-art performance in the DID field.The code will be available on GitHub upon the paper's acceptance.
基金supported by the National Natural Science Foundation of China(Nos.81730107 and 81973883)the National Science&Technology Basic Research Project(No.2015FY111700)the Shanghai Pudong New District New Area Project(No.PW2022A-78(WQZ)).
文摘Objectives:By investigating the distinct speech and voice phenotype among TCM constitution for adults,this study aims at providing a convenient and objective methodological reference for judging TCM constitution.Methods:Acoustic analysis and TCM constitution assessment were performed for all 620 participants using Praat software and the CCMQ,respectively.Results:For formant features,the speech duration of special constitution participants was shorter than that of neutral,phlegm-dampness,dampness-heat,Yin-deficiency,or Yang-deficiency participants when pronuncing the vowels/a/,/i/,and/u/.Compare to Yang-deficiency,Qi-deficiency participants had a shorter speech duration when pronucing/i/.For/u/,blood-stasis participants exhibited a lower F1 value than neutral participants.For vocal features,special constitution participants showed higher local jitter than neutral,dampness-heat,and Yang-deficiency participants(for/a/,/i/,and/u/).Higher absolute local jitter than neutral or dampness-heat participants.Compared with neutral or Yang-deficiency participants,special participants owned a higher local shimmer(dB).Special participants had a lower harmonicity autocorrelation than neutral,dampness-heat,or Yang-deficiency participants.Conclusions:Formant features may effectively differentiate special constitution from neutral,phlegm-dampness,dampness-heat,Yin-deficiency,or Yang-deficiency constitutions based on vowel duration measurements(/a/,/i/,/u/).For the vowel/u/,F1 values may help distinguish blood-stasis from neutral constitution.Vocal features appear particularly useful for distinguishing special constitution from neutral,dampness-heat,or Yang-deficiency constitution,with local jitter and harmonicity autocorrelation showing significant discriminatory power.
文摘Forests are essential for both ecological and economic aspects.Most rural people in developing countries rely on forest resources for their livelihood.Since 1980,trade has substantially affected forest cover,density,and management in developing countries.Few studies have examined how changes in trade structure and international trade in primary commodities affect forest density.To better understand the relationship between trade,trade structure adjustment,and forest density,this study examined 52 developing countries across four income levels:high income(HI),low income(LI),upper-middle income(UMI),and lower-middle income(LMI).We compared studies on historical changes in forest cover with those on forest density.For alternative outcomes,we used a generalized method of moments(GMM)model for the entire panel and a random-effects model for various income categories.The results show that the percentage of non-primary goods exported(PNPEXP)and total manufacturing and services exported(TEXP)significantly impact forest density.This suggests that trade and trade structure can improve a country’s forest density conditions.
文摘As global economic integration development enters a realization era,English holds a very important position in China's diplomacy as the language is an internationally-used language.Besides,English also plays a very important role in our daily life.Colleges and universities should pay more attention in strengthening the development of English teaching courses as they are an important base for cultivating high-quality talents.In the modern teaching of English and American literature courses,college English majors do not only need to teach students English language knowledge but are also required need to strengthen students'knowledge and study of national culture.In this journal,the author investigates and analyses the current situation and existing problems of the modern teaching of English and American literature courses in English majors of colleges and universities.Then,puts forward the implementation strategies such as modern teaching of English and American literature courses in English majors’colleges and universities,aiming to help in implementing the teaching of English and American literature courses successfully.
文摘As global economic integration development enters a realization era,English holds a very important position in China's diplomacy as the language is an internationally-used language.Besides,English also plays a very important role in our daily life.Colleges and universities should pay more attention in strengthening the development of English teaching courses as they are an important base for cultivating high-quality talents.In the modern teaching of English and American literature courses,college English majors do not only need to teach students English language knowledge but are also required need to strengthen students'knowledge and study of national culture.In this journal,the author investigates and analyses the current situation and existing problems of the modern teaching of English and American literature courses in English majors of colleges and universities.Then,puts forward the implementation strategies such as modern teaching of English and American literature courses in English majors’colleges and universities,aiming to help in implementing the teaching of English and American literature courses successfully.
文摘In the contemporary era,the death rate is increasing due to lung cancer.However,technology is continuously enhancing the quality of well-being.To improve the survival rate,radiologists rely on Computed Tomography(CT)scans for early detection and diagnosis of lung nodules.This paper presented a detailed,systematic review of several identification and categorization techniques for lung nodules.The analysis of the report explored the challenges,advancements,and future opinions in computer-aided diagnosis CAD systems for detecting and classifying lung nodules employing the deep learning(DL)algorithm.The findings also highlighted the usefulness of DL networks,especially convolutional neural networks(CNNs)in elevating sensitivity,accuracy,and specificity as well as overcoming false positives in the initial stages of lung cancer detection.This paper further presented the integral nodule classification stage,which stressed the importance of differentiating between benign and malignant nodules for initial cancer diagnosis.Moreover,the findings presented a comprehensive analysis of multiple techniques and studies for nodule classification,highlighting the evolution of methodologies from conventional machine learning(ML)classifiers to transfer learning and integrated CNNs.Interestingly,while accepting the strides formed by CAD systems,the review addressed persistent challenges.
基金Project(IFP-A-2022-2-5-24) supported by Institutional Fund Projects,University of Hafr Al Batin,Saudi Arabia。
文摘This article studies the influence of polymers on drag reduction and heat transfer enhancement of a nanofluid past a uniformly heated permeable vertically stretching surface. Our prime focus is on analyzing the possible effects of polymer inclusion in the nanofluid on drag coefficient, Nusselt number and Sherwood number. Dispersion model is considered to study the behavior of fluid flow and heat transfer in the presence of nanoparticles. Molecular approach is opted to explore polymer addition in the base fluid. An extra stress arises in the momentum equation as an outcome of polymer stretching. The governing boundary layer equations are solved numerically. Dependence of physical quantities of engineering interest on different flow parameters is studied. Reduction in drag coefficient, Nusselt number and Sherwood number is noticed because of polymer additives.
基金This research is funded by Taif University, TURSP-2020/115.
文摘:Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and services.The increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making process.To overcome this challenge,extracting suggestions from opinionated text is a possible solution.In this study,the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’reviews.A classification using a word-embedding approach is used via the XGBoost classifier.The two datasets used in this experiment relate to online hotel reviews and Microsoft Windows App Studio discussion reviews.F1,precision,recall,and accuracy scores are calculated.The results demonstrated that the XGBoost classifier outperforms—with an accuracy of more than 80%.Moreover,the results revealed that suggestion keywords and phrases are the predominant features for suggestion extraction.Thus,this study contributes to knowledge and practice by comparing feature extraction classifiers and identifying XGBoost as a better suggestion mining process for identifying online reviews.
文摘The feedback collection and analysis has remained an important subject matter for long.The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis.However,the student expresses their feedback opinions on online social media sites,which need to be analyzed.This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews.Our technique computes the sentiment score of student feedback reviews and then applies a fuzzy-logic module to analyze and quantify student’s satisfaction at the fine-grained level.The experimental results reveal that the proposed work has outperformed the baseline studies as well as state-of-the-art machine learning classifiers.
基金‘This research is funded by Taif University,TURSP-2020/115’.
文摘Software crowdsourcing(SW CS)is an evolving software development paradigm,in which crowds of people are asked to solve various problems through an open call(with the encouragement of prizes for the top solutions).Because of its dynamic nature,SW CS has been progressively accepted and adopted in the software industry.However,issues pertinent to the understanding of requirements among crowds of people and requirements engineers are yet to be clarified and explained.If the requirements are not clear to the development team,it has a significant effect on the quality of the software product.This study aims to identify the potential challenges faced by requirements engineers when conducting the SW–CS based requirements engineering(RE)process.Moreover,solutions to overcome these challenges are also identified.Qualitative data analysis is performed on the interview data collected from software industry professionals.Consequently,20 SW–CS based RE challenges and their subsequent proposed solutions are devised,which are further grouped under seven categories.This study is beneficial for academicians,researchers and practitioners by providing detailed SW–CS based RE challenges and subsequent solutions that could eventually guide them to understand and effectively implement RE in SW CS.
基金This study is financed by the grant from Lehigh University,College of Arts and Sciences,NEH distinguished scholar fund.
文摘This essay will review the earliest case that documents a patient’s experience of qi,one found on a bamboo text buried with the patient who died in the 318 BCE.Details of the healing encounter and of concepts of illness show how non-transmitted documents hidden from later editors in tombs preserve an older layer of medical understanding than that in transmitted canons,such as the Huang Di Nei Jing(Inner Canon of the Yellow Emperor).The 4th-century BCE case record described below is the longest early medical record concerning the treatment of a specific individual.It is also an account of failure formally recorded for the sake of the survivors and buried with the dead to be transmitted to the world of the spirits.The essay begins with a reevaluation of ancient concept of qi and then moves on to the individual case record.
文摘The Internet of Things(IoT)is gaining attention because of its broad applicability,especially by integrating smart devices for massive communication during sensing tasks.IoT-assisted Wireless Sensor Networks(WSN)are suitable for various applications like industrial monitoring,agriculture,and transportation.In this regard,routing is challenging to nd an efcient path using smart devices for transmitting the packets towards big data repositories while ensuring efcient energy utilization.This paper presents the Robust Cluster Based Routing Protocol(RCBRP)to identify the routing paths where less energy is consumed to enhances the network lifespan.The scheme is presented in six phases to explore ow and communication.We propose the two algorithms:(i)energy-efcient clustering and routing algorithm and (ii)distance and energy consumption calculation algorithm.The scheme consumes less energy and balances the load by clustering the smart devices.Our work is validated through extensive simulation using Matlab.Results elucidate the dominance of the proposed scheme is compared to counterparts in terms of energy consumption,the number of packets received at BS and the number of active and dead nodes.In the future,we shall consider edge computing to analyze the performance of robust clustering.
文摘Throughout the use of the small battery-operated sensor nodes encou-rage us to develop an energy-efficient routing protocol for wireless sensor networks(WSNs).The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of WSN.Many routing protocols are available,but the issue is still alive.Clustering is one of the most important techniques in the existing routing protocols.In the clustering-based model,the important thing is the selection of the cluster heads.In this paper,we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining energy and the distance of the nodes in each cluster.Initially,the bubble sort algorithm chose the two nodes with the maximum remaining energy in the cluster and chose a cluster head with a small distance.The proposed scheme performs hierarchal routing and direct routing with some energy thresholds.The simulation will be performed in MATLAB to justify its performance and results and compared with the ECHERP model to justify its performance.Moreover,the simulations will be performed in two scenarios,gate-way-based and without gateway to achieve more energy-efficient results.
基金The authors extend their appreciation to National University of Sciences and Technology for funding this work through Researchers Supporting Grant,National University of Sciences and Technology,Islamabad,Pakistan.
文摘With the advent and advancements in the wireless technologies,Wi-Fi ngerprinting-based Indoor Positioning System(IPS)has become one of the most promising solutions for localization in indoor environments.Unlike the outdoor environment,the lack of line-of-sight propagation in an indoor environment keeps the interest of the researchers to develop efcient and precise positioning systems that can later be incorporated in numerous applications involving Internet of Things(IoTs)and green computing.In this paper,we have proposed a technique that combines the capabilities of multiple algorithms to overcome the complexities experienced indoors.Initially,in the database development phase,Motley Kennan propagation model is used with Hough transformation to classify,detect,and assign different attenuation factors related to the types of walls.Furthermore,important parameters for system accuracy,such as,placement and geometry of Access Points(APs)in the coverage area are also considered.New algorithm for deployment of an additional AP to an already existing infrastructure is proposed by using Genetic Algorithm(GA)coupled with Enhanced Dilution of Precision(EDOP).Moreover,classication algorithm based on k-Nearest Neighbors(k-NN)is used to nd the position of a stationary or mobile user inside the given coverage area.For k-NN to provide low localization error and reduced space dimensionality,three APs are required to be selected optimally.In this paper,we have suggested an idea to select APs based on Position Vectors(PV)as an input to the localization algorithm.Deducing from our comprehensive investigations,it is revealed that the accuracy of indoor positioning system using the proposed technique unblemished the existing solutions with signicant improvements.
基金This work has partially been sponsored by the Hungarian National Scientific Fund under contract OTKA 129374the Research&Development Operational Program for the project“Modernization and Improvement of Technical Infrastructure for Research and Development of J.Selye University in the Fields of Nanotechnology and Intelligent Space”,ITMS 26210120042,co-funded by the European Regional Development Fund.
文摘Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions.However,most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets,resulting in performance degradation.To overcome this issue,this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset.The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision,recall ad f-measure.Finally,a classifier with the best performance is recommended for the emotion classification.
基金the Natural Science Foundation of China(Grant Nos.61673169,11301127,11701176,11626101,and 11601485)The Natural Science Foundation of Huzhou City(Grant No.2018YZ07).
文摘In this article,we construct the most powerful family of simultaneous iterative method with global convergence behavior among all the existing methods in literature for finding all roots of non-linear equations.Convergence analysis proved that the order of convergence of the family of derivative free simultaneous iterative method is nine.Our main aim is to check out the most regularly used simultaneous iterative methods for finding all roots of non-linear equations by studying their dynamical planes,numerical experiments and CPU time-methodology.Dynamical planes of iterative methods are drawn by using MATLAB for the comparison of global convergence properties of simultaneous iterative methods.Convergence behavior of the higher order simultaneous iterative methods are also illustrated by residual graph obtained from some numerical test examples.Numerical test examples,dynamical behavior and computational efficiency are provided to present the performance and dominant efficiency of the newly constructed derivative free family of simultaneous iterative method over existing higher order simultaneous methods in literature.
文摘The paper focuses on the properties of relative pronouns in the acquisition of relative clause by Chinese EFL learners. Based on the NPAH （noun phrase accessibility hierarchy）, comparison and contrast of some aspects of English and Chinese relative pronoun, the paper conducts two experiments, and has proved the hypotheses that students＇ performance generally follows the hierarchy of NPAH and students do have problems with relative pronoun involving prepositions. Besides, some pedagogical implications for foreign language teaching are discussed.
